CN105718441A - Method and device for searching UI modules with similar functions between different platforms - Google Patents
Method and device for searching UI modules with similar functions between different platforms Download PDFInfo
- Publication number
- CN105718441A CN105718441A CN201610019895.2A CN201610019895A CN105718441A CN 105718441 A CN105718441 A CN 105718441A CN 201610019895 A CN201610019895 A CN 201610019895A CN 105718441 A CN105718441 A CN 105718441A
- Authority
- CN
- China
- Prior art keywords
- assembly
- module
- similarity
- word
- document
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 20
- 230000006870 function Effects 0.000 title abstract description 13
- 239000013598 vector Substances 0.000 claims abstract description 22
- 238000005516 engineering process Methods 0.000 abstract description 8
- 238000012545 processing Methods 0.000 abstract description 2
- 230000014509 gene expression Effects 0.000 abstract 2
- 230000000877 morphologic effect Effects 0.000 abstract 2
- 230000003247 decreasing effect Effects 0.000 abstract 1
- 238000011161 development Methods 0.000 description 7
- 238000013461 design Methods 0.000 description 3
- 230000000052 comparative effect Effects 0.000 description 2
- 238000005065 mining Methods 0.000 description 2
- 238000003058 natural language processing Methods 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000000712 assembly Effects 0.000 description 1
- 238000000429 assembly Methods 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
- G06F40/216—Parsing using statistical methods
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Probability & Statistics with Applications (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Computational Linguistics (AREA)
- General Health & Medical Sciences (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Machine Translation (AREA)
Abstract
The invention discloses a method and device for searching UI modules with similar functions between different platforms. The method comprises the following steps: extracting keywords by carrying out text analysis on documents of the UI modules, recording the word frequency of each keyword, carrying out morphological reduction on the keywords, and carrying out synonym combination on the reduced keywords so as to obtain characteristic keywords and corresponding word frequency to construct characteristic vectors; and calculating the similarity between the UI modules of two different platforms according to the characteristic vector corresponding to each UI. According to the method and device, morphological reduction is carried out on the words and expressions in the documents, and through a stem extracting technology, the words and expressions in different forms are summed into a keyword, so that not only the dimensions of the keywords are decreased, but better similarity comparing result also can be generated; and through the processing carried out on the synonyms in the texts, the similarity of the similar texts can be increased.
Description
Technical field
The present invention relates to the application in soft project of natural language processing and Text Mining Technology.
Background technology
At present, along with quickly popularizing of large-size screen monitors smart mobile phone, Mobile solution market development is rapid, presents situation multi-platform, multi version.Generally having the version on multiple platform with a application, the function that these application presented and completed is substantially coincident.A kind of scene of developing that presently, there are is first to develop the APP, the APP of other platforms of then redeveloping of a platform.And the method developed respectively is mostly taked at industrial quarters APP, inefficient.Based on an existing platform release, help exploitation another one platform release, it is possible to be greatly enhanced development efficiency, reduce development cost.
On large-size screen monitors smart mobile phone, the operation of APP is mainly driven by interface event, and some UI assemblies that user clicks or shows on slip screen carry out operating handset.By studying the correspondence at interface of Mobile solution, namely study the correspondence of different platform Mobile solution UI assembly, can the existing INTERFACE DESIGN of multiplexing, the operation control flow and nanocode backbone that are applied on new platform can be built again.
At present only the official document of each platform very comprehensively detailed can introduce UI assembly, and official document here includes the document of introducing for UI assembly function, outward appearance, use etc., the API document etc. of UI assembly class.Therefore understands that the main method of the similarity of different platform UI assembly is to obtain relevant knowledge by reading its official document.
Text mining is to extract valuable knowledge effective, novel, useful, intelligible, that be dispersed in text, and utilizes the process of the better organizational information of these knowledge.Nowadays text-processing technology is very ripe, for instance Chinese and English participle, synonym compare.Simultaneously natural language processing technique is fast-developing, and the technology such as the extraction of lemmatization, stem, part-of-speech tagging achieves certain progress.Data mining technology there has also been very big development, and various features represents that model can use.The development of these technology allows us to find the correspondence between different platform UI assembly from the substantial amounts of document relevant to UI assembly.
Summary of the invention
Problem to be solved by this invention is quickly to search UI assembly, and helper applications developer designs and realizes APP.
For solving the problems referred to above, the scheme that the present invention adopts is as follows:
A kind of according to the present invention searches the method for functional similarity UI assembly between different platform, and the method comprises the following steps:
Step 1, obtains the document corresponding to the UI assembly of each platform and UI assembly；
Step 2, carries out text analyzing and obtains characteristic key words, the characteristic vector of composition UI assembly the document of UI assembly；
Step 3, according to the characteristic vector that step 2 obtains, calculates the similarity of the UI inter-module of two different platforms；
Step 4, repeats step 3 until calculating the similarity of the UI inter-module of any two different platform；
Step 5, is ranked up the similarity of the UI inter-module of any two different platform.
Further, according to the method for functional similarity UI assembly between the lookup different platform of the present invention, described step 2 comprises the following steps:
Step 21, by the document of UI assembly is made pauses in reading unpunctuated ancient writings, after participle, is named word, verb, adjective and adverbial word as key word, and records the word frequency number that each key word occurs；
Step 22, to carrying out synonym and near synonym merging after key word lemmatization.
A kind of according to the present invention searches the device of functional similarity UI assembly between different platform, and this device includes:
Module 1, is used for obtaining the document corresponding to the UI assembly of each platform and UI assembly；
Module 2, obtains characteristic key words, the characteristic vector of composition UI assembly for the document of UI assembly carries out text analyzing；
Module 3, for the characteristic vector that module 2 obtains, calculates the similarity of the UI inter-module of two different platforms；
Module 4, for repeating calling module 3 until calculating the similarity of the UI inter-module of any two different platform；
Module 5, for being ranked up the similarity of the UI inter-module of any two different platform.
Further, according to the device of functional similarity UI assembly between the lookup different platform of the present invention, it is characterised in that described module 2 includes:
Module 21, for by the document of UI assembly is made pauses in reading unpunctuated ancient writings, after participle, being named word, verb, adjective and adverbial word as key word, and record the word frequency number that each key word occurs；
Module 22, for carrying out synonym and near synonym merging after key word lemmatization.
The technique effect of the present invention is as follows:
1, relative to traditional text similarity comparative approach being based only in document word occurrence number, the present invention word to occurring in document adopts lemmatization, stem extractive technique makes multi-form word sum up a key word, not only reduces the dimension of key word and can produce better similar comparative result；Process synon in text more can be increased the similarity size of Similar Text by the present invention.
2, the similar situation between different mobile platform UI assembly is excavated, it is possible to helper applications designer understands the relation between each platform UI assembly.
3, the UI assembly of other platforms similar to current UI assembly is searched, thus helper applications developer quickly quickly designs the interface of another one platform release APP based on the interface of an existing platform release APP, development efficiency can be greatly enhanced, reduce development cost.
Detailed description of the invention
Below the present invention is described in further details.
Step 1, the function that namely aforementioned modules 1 realizes, obtain the document corresponding to the UI assembly of each platform and UI assembly.What " acquisition " here represented is " document corresponding to the UI assembly of each platform and UI assembly " is the input of the present invention." how to obtain the document corresponding to the UI assembly of each platform and UI assembly " and be not the category that the present invention is discussed.In being embodied as, " document corresponding to the UI assembly of each platform and UI assembly " can pass through web crawlers instrument and automatically collect, it is also possible to as the input of the present invention after being collected by artificial mode and arranged.This input can represent by following data structure:
Input_set={(uiNamei,uiDoci)|i∈[1..N]}。
Wherein, uiNameiFor the UI assembly represented with name field, uiDociFor the document corresponding to UI assembly, N is UI package count.Here document includes but not limited to introduce document and the API document etc. of UI assembly class for UI assembly function, outward appearance, use etc., typically from the official document illustrated about UI assembly function on platform.Document corresponding to UI assembly can be the forms such as HTML, XML, DOC, it is also possible to is Rich Text Format.In general, the document of the form such as HTML, XML, DOC, Rich Text Format can be converted in step 1 as input.
Step 2, the function that namely aforementioned modules 2 realizes, the document of UI assembly is carried out text analyzing and obtains characteristic key words, the characteristic vector of composition UI assembly.Step 2 is the document text natural language analysis process of an automatization.Here the input in document text namely step 1: { uiDoci| i ∈ [1..N] }.First pass through the document to UI assembly to make pauses in reading unpunctuated ancient writings, after participle, be named word, verb, adjective and adverbial word as key word, and record the word frequency number that each key word occurs namely the function that step 21 and module 21 realize.Participle and judge when whether part of speech is noun, verb, adjective and adverbial word, it is possible to foundation dictionary carries out, and this technology being familiar with for those skilled in the art, this specification repeats no more.The output of step 21 can be expressed as:
{Word_seti| i ∈ [1..N] }, wherein Word_seti={(WordJ, i,freqJ, i)|j∈[1..Wi]}。
Wherein, Word_setiKeyword set for i-th UI assembly；WordJ, iJth key word for i-th UI assembly；FreqJ, iFor the word frequency number of the jth key word of i-th UI assembly, namely key word WordjAt uiDociMiddle occurred frequency number；WiKey word number for i-th UI assembly.
Then, step 22, the function that namely module 22 realizes, to carrying out synonym and near synonym merging after key word lemmatization.Here " key word lemmatization " has allowed for the problem that there is the different terms form such as tense and gerund in English, such as " search " in " searching ", " find " in " found "." searching " and " found " just becomes " search " and " find " after carrying out lemmatization." synonym and near synonym merge " includes two steps:
Step 221, synonym and the near synonym of each different UI inter-modules are replaced；
Step 222, the synonym of same UI inter-module and the merging of near synonym.
Such as, " search " and " find " is close, then in step 221, by { Word_seti| i ∈ [1..N] } in all of WordJ, iIn " find " replace to " search ".After the replacement of step 221, it is understood that there may be same Word_setiIn WordJ, iIdentical, now need to be merged.This merging process is step 222.Such as after step 221 is replaced, WordA, iAnd WordB, iIt is " search ", then deletes WordB, iAnd by WordB, iCorresponding word frequency number freqB, iAdd to freqA, iMiddle formation KeyfreqA, i, revise the number W of key word simultaneouslyi.It is hereby achieved that new characteristic key words and characteristic vector output:
{Keyword_vecti| i ∈ [1..N] }, wherein Keyword_vecti={(KeywordJ, i, KeyfreqJ, i)|j∈[1..Ki]}。
Wherein, Keyword_vectiFor the feature critical set of words of i-th UI assembly, also it is the characteristic vector of i-th UI assembly；KeywordJ, iJth characteristic key words for i-th UI assembly；KeyfreqJ, iWord frequency number for the jth characteristic key words of i-th UI assembly；KiKey word number for i-th UI assembly.
Step 3, namely the function that aforementioned modules 3 realizes, the characteristic vector that step 2 obtains, calculate the similarity of the UI inter-module of two different platforms.The input of this step be step 2 characteristic vector Keyword_vect in outputi, i ∈ [1..N]." calculate the similarity of the UI inter-module of two different platforms " namely calculate two different characteristic vector Keyword_vectaAnd Keyword_vectbBetween similarity.Two characteristic vector Keyword_vectaAnd Keyword_vectbBetween the calculating of similarity can adopt following steps: step 31, according to two characteristic vector Keyword_vectaAnd Keyword_vectb, build corresponding Euler space Sa,b；Step 32, respectively to characteristic vector Keyword_vectaAnd Keyword_vectbAt Euler space Sa,bInterior normalized；Step 33, calculates the characteristic vector Keyword_vect after normalizationaAnd Keyword_vectbAt Euler space Sa,bDistance D between interiora,b, finally calculate 1-Da,bAs two characteristic vector Keyword_vectaAnd Keyword_vectbBetween similarity.Characteristic vector Keyword_vectaAnd Keyword_vectbBetween the calculating of similarity obtain result, the namely similarity between the document of UI assembly.The present invention is using the similarity as UI inter-module of the similarity between the document of UI assembly.The similarity of UI inter-module can represent with percent.
Step 4, namely the function that aforementioned modules 4 realizes, repeat step 3 until calculating the similarity of the UI inter-module of any two different platform.This step is loop control step, is familiar with by those skilled in the art, repeats no more.
Step 5, namely the function that aforementioned modules 5 realizes, be ranked up the similarity of the UI inter-module of any two different platform.The arrangement of the similarity of the obtained UI inter-module of abovementioned steps 3 and step 4 is shown by this step.Sort algorithm is familiar with by those skilled in the art, and this specification repeats no more.
Claims (4)
1. search the method for functional similarity UI assembly between different platform for one kind, it is characterised in that the method comprises the following steps:
Step 1, obtains the document corresponding to the UI assembly of each platform and UI assembly；
Step 2, carries out text analyzing and obtains characteristic key words, the characteristic vector of composition UI assembly the document of UI assembly；
Step 3, according to the characteristic vector that step 2 obtains, calculates the similarity of the UI inter-module of two different platforms；
Step 4, repeats step 3 until calculating the similarity of the UI inter-module of any two different platform；
Step 5, is ranked up the similarity of the UI inter-module of any two different platform.
2. the method for functional similarity UI assembly between lookup different platform as claimed in claim 1, it is characterised in that described step 2 comprises the following steps:
Step 21, by the document of UI assembly is made pauses in reading unpunctuated ancient writings, after participle, is named word, verb, adjective and adverbial word as key word, and records the word frequency number that each key word occurs；
Step 22, to carrying out synonym and near synonym merging after key word lemmatization.
3. search the device of functional similarity UI assembly between different platform for one kind, it is characterised in that this device includes:
Module 1, is used for obtaining the document corresponding to the UI assembly of each platform and UI assembly；
Module 2, obtains characteristic key words, the characteristic vector of composition UI assembly for the document of UI assembly carries out text analyzing；
Module 3, for the characteristic vector obtained according to module 2, calculates the similarity of the UI inter-module of two different platforms；
Module 4, for repeating calling module 3 until calculating the similarity of the UI inter-module of any two different platform；
Module 5, for being ranked up the similarity of the UI inter-module of any two different platform.
4. the device of functional similarity UI assembly between lookup different platform as claimed in claim 3, it is characterised in that described module 2 includes:
Module 21, for by the document of UI assembly is made pauses in reading unpunctuated ancient writings, after participle, being named word, verb, adjective and adverbial word as key word, and record the word frequency number that each key word occurs；
Module 22, for carrying out synonym and near synonym merging after key word lemmatization.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610019895.2A CN105718441B (en) | 2016-01-13 | 2016-01-13 | The method and apparatus of the similar UI components of function between a kind of lookup different platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610019895.2A CN105718441B (en) | 2016-01-13 | 2016-01-13 | The method and apparatus of the similar UI components of function between a kind of lookup different platform |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105718441A true CN105718441A (en) | 2016-06-29 |
| CN105718441B CN105718441B (en) | 2018-10-23 |
Family
ID=56147790
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610019895.2A Active CN105718441B (en) | 2016-01-13 | 2016-01-13 | The method and apparatus of the similar UI components of function between a kind of lookup different platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105718441B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106844339A (en) * | 2017-01-09 | 2017-06-13 | 南京大学 | A kind of multi-platform control corresponding method based on term vector |
| CN111694568A (en) * | 2019-03-15 | 2020-09-22 | 阿里巴巴集团控股有限公司 | Method and device for generating UI card document |
| CN112116011A (en) * | 2020-09-21 | 2020-12-22 | 上海晓材科技有限公司 | Feature coding method and similarity comparison method for CAD graph |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103136355A (en) * | 2013-03-05 | 2013-06-05 | 电子科技大学 | Text clustering method on basis of automatic threshold fish swarm algorithm |
| CN104102626A (en) * | 2014-07-07 | 2014-10-15 | 厦门推特信息科技有限公司 | Method for computing semantic similarities among short texts |
-
2016
- 2016-01-13 CN CN201610019895.2A patent/CN105718441B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103136355A (en) * | 2013-03-05 | 2013-06-05 | 电子科技大学 | Text clustering method on basis of automatic threshold fish swarm algorithm |
| CN104102626A (en) * | 2014-07-07 | 2014-10-15 | 厦门推特信息科技有限公司 | Method for computing semantic similarities among short texts |
Non-Patent Citations (3)
| Title |
|---|
| ANDREAS RUMPEL等: "Platform Adaptation of Mashup UI Components", 《ADAPTIVE 2010 : THE SECOND INTERNATIONAL CONFERENCE ON ADAPTIVE AND SELF-ADAPTIVE SYSTEMS AND APPLICATIONS》 * |
| RONALD VAN BEZU等: "Multi-component similarity method for web product duplicate detection", 《SAC "15 PROCEEDINGS OF THE 30TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING》 * |
| 蒋勇铭等: "一种基于可复用控件的UI开发方法", 《电脑知识与技术》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106844339A (en) * | 2017-01-09 | 2017-06-13 | 南京大学 | A kind of multi-platform control corresponding method based on term vector |
| CN106844339B (en) * | 2017-01-09 | 2020-04-28 | 南京大学 | Word vector-based multi-platform control corresponding method |
| CN111694568A (en) * | 2019-03-15 | 2020-09-22 | 阿里巴巴集团控股有限公司 | Method and device for generating UI card document |
| CN111694568B (en) * | 2019-03-15 | 2023-04-07 | 阿里巴巴集团控股有限公司 | Method and device for generating UI card document |
| CN112116011A (en) * | 2020-09-21 | 2020-12-22 | 上海晓材科技有限公司 | Feature coding method and similarity comparison method for CAD graph |
| CN112116011B (en) * | 2020-09-21 | 2021-07-27 | 上海晓材科技有限公司 | Feature coding method and similarity comparison method for CAD graph |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105718441B (en) | 2018-10-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11379548B2 (en) | Analyzing concepts over time | |
| Täckström et al. | Efficient inference and structured learning for semantic role labeling | |
| US11017301B2 (en) | Obtaining and using a distributed representation of concepts as vectors | |
| US10073840B2 (en) | Unsupervised relation detection model training | |
| US11521603B2 (en) | Automatically generating conference minutes | |
| US20140324808A1 (en) | Semantic Segmentation and Tagging and Advanced User Interface to Improve Patent Search and Analysis | |
| CN107690634B (en) | Automatic query pattern generation method and system | |
| US20210374344A1 (en) | Method for resource sorting, method for training sorting model and corresponding apparatuses | |
| CN102609427A (en) | Public opinion vertical search analysis system and method | |
| WO2021000391A1 (en) | Text intelligent cleaning method and device, and computer-readable storage medium | |
| CN102214189A (en) | Data mining-based word usage knowledge acquisition system and method | |
| CN107526721A (en) | A kind of disambiguation method and device to electric business product review vocabulary | |
| CN105718441A (en) | Method and device for searching UI modules with similar functions between different platforms | |
| US20210034621A1 (en) | System and method for creating database query from user search query | |
| CN114141384A (en) | Method, apparatus and medium for retrieving medical data | |
| CN106021413A (en) | Theme model based self-extendable type feature selecting method and system | |
| CN111191413A (en) | Method, device and system for automatically marking event core content based on graph sequencing model | |
| US20140164432A1 (en) | Ontology enhancement method and system | |
| TW201822031A (en) | Method of creating chart index with text information and its computer program product capable of generating a virtual chart message catalog and schema index information to facilitate data searching | |
| JP4014130B2 (en) | Glossary generation device, glossary generation program, and glossary search device | |
| JP2008276561A (en) | Morpheme analysis device, morpheme analysis method, morpheme analysis program, and recording medium with computer program recorded thereon | |
| CN111552576B (en) | Insertion and ingestion framework for question-answering system | |
| Dais et al. | A Comparison on Techniques for Automatic Generation of Presentation Slides | |
| Garcia-Silva et al. | Semantic Technologies and Text Analysis in Support of Scientific Knowledge Reuse | |
| Borkakoty et al. | A Naive Extractive Text Summarizer for Assamese Language |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |